Predictive Modeling and Analytics

In this highly competitive global environment, any professional and progressive organization that aims to survive and grow significantly in the marketplace must unshackle itself from ad hoc ways of prediction. Instead, it should use analytic models for accurate prediction so that the models can borrow strength from part data. It is in this context, the role of predictive modeling is important in business context. Predictive Modeling embraces a variety of techniques that can be used by organizations to predict continuous (Sales or Demand) as well as categorical (Buyer or Non-Buyer) dependent variables based on a host of input variables (Independent Variables).

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Skills you will gain

  • Linear Regression
  • Logistic Regression
  • Discriminant Analysis

Course Syllabus

Module 1

Predictive Modeling and Analytics

7.0 Hrs

3 Quizzes
  • Overview of Predictive Modelling
  • Understanding Regression
  • Regression using R
  • Logistic Regression
  • Logistic Regression using R
  • Introduction to Linear Discriminant Analysis (LDA)
  • LDA in R
  • Frequency Based Algorithm
  • Frequency Based Algorithms in R
  • Model Comparison
  • Cross Validation
  • Cross Validation in R


Predict future election outcomes

Course certificate

Get Predictive Modeling and Analytics course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.